1. Field of the Invention
The present invention relates to search engines, and more particularly, to search engine methods and systems that provide personalized contextual search results.
2. Background of Invention
The emergence of the Information Age has created a wealth of information that is available electronically. Unfortunately, much of this information is often inaccessible to individuals because they do not know where to look for it, or if they do know where to look the information can not be found efficiently. For example, an individual is working at his desk and his boss requests that he find an electronic copy of a memo that the individual sent last month. The memo contains information that was obtained from a website, which included a spreadsheet that had data extracted from a division report.
The boss would like the individual to send a copy of the email and the references back to him as soon as possible. Also, he would like the individual to check for additional references to see if the conclusions in the memo need to be updated. The boss requires that the project be completed within fifteen minutes. The worker is not disorganized, but as is common, does not have total recall of how the information was gathered or where the email is stored. After thirty minutes, the worker finally finds the email. But, the worker still needs to search for additional information as requested by his boss. The end result is that because no efficient search mechanism existed the worker has missed his boss' deadline.
The above example commonly occurs within the workplace, and involves not just email, but all forms of electronically stored information. Human worker studies show that it is not unusual for some office workers to spend more than 10% of each work day looking for information. The same studies claim that less than half those searches are successful. Databases, data warehouses, document management systems, and file searches are often too difficult or “hit and miss” to be used effectively and efficiently. Corporate enterprises and government organizations have spent billions of dollars to aggregate and integrate information, so it will be more accessible. Of course, an individual can get answers if he is a database or document system expert and if the individual remembers the exact title, the exact phrasing used in the document, or the ever elusive primary key associated with the document of interest. Unfortunately, more common than not, this level of detail is not available to assist in finding the information.
Internet based searches are often times even more frustrating, and less productive. For example, it is not particularly useful when you know that there are approximately 6,120,000 answers to the search criteria you just entered. Furthermore, because website popularity has nothing to do with what might be relevant in the thousands of search results, search results driven by website popularity can often lead to useless results. Meanwhile, at search engine operations facility there is an army of personnel and massive server farms humming away to potentially deliver hundreds of thousands of results to every search query that an individual enters.
Web searching, search advertising, and enterprise searching are not consistently providing acceptable search resolution for the user. The missing ingredient in current search technology is “true relevance”. Relevance can only be defined by the user for a specific search. Relevancy has no predictable pattern. No generalized algorithm is going to repeatably produce relevant information, because in the end, any generalization is arbitrary.
What are needed are search methods and systems that can efficiently generate search results that are relevant to the particular user's interest within their context of interest.